Figure 1: The homoclinic pulse solution of (4) for and . Here, the scaled pulses and are plotted on the long spatial scale . The singular `sharp' pulse represents the -component, it is close to a homoclinic solution of the scalar equation (1) with (Theorem 1). This figure has been obtained by direct numerical simulation of (4) using the moving-grid code described in [2].

Although pulse solutions of scalar equations can thus never be stable, there are many systems of PDEs, such as the Gray-Scott model for autocatalytic reactions [7] and the Gierer-Meinhardt model, that exhibit pulse solutions that are very similar to scalar pulses, see Figure 1. These systems can be written in the following form

(3)

where is an asymptotically small parameter. Since both and are assumed to be bounded for - a natural condition for solutions to PDEs on unbounded domains - it follows that , a constant, as . Hence, (3) reduces to (1), with in the limit . Note that a coupled system of reaction-diffusion equations in which the ratio of the diffusion coefficients can be assumed to be small, as is the case for the Gray-Scott and the Gierer-Meinhardt model, can always be written in the form (3).

The limit intuitively yields two conclusions for the situation : *(i)* it can be expected that (3) indeed has solutions of pulse type of which the -component is close to a pulse solution of a scalar PDE (1); *(ii)* the pulse solution can also not be stable: the spectrum of the linearization around should be close to that of the scalar case (which has an unstable eigenvalue). In general, neither of these assertions is (completely) true. Moreover, both the existence *(i)* and the stability *(ii)* question require the development of novel ideas and techniques. For instance, the scalar problem (1) with will have a pulse solution for open -sets, the limit procedure is expected to select only a discrete number of the 's and the corresponding pulses . However, the ODE associated to the stationary problem for the PDE (3) is a dynamical system in . A priori, there are no general techniques by which the existence of homoclinic orbits in such problems can be established. Furthermore, the stability problem yields a linear system that is neither of Sturm-Liouville type, nor self-adjoint, which implies that one should expect complex eigenvalues . Moreover, the Sturm-Liouville equation (2) associated to the scalar limit indeed is a singular limit, the `perturbations' due to the coupling to the additional slow diffusion equation for have a leading order effect on the eigenvalues. In other words: the coupling of to a slow diffusion equation for might be able to bring the unstable eigenvalue of the scalar limit problem to the stable half-plane.

As an example we present here two theorems that settle both the the existence problem and the stability problem in the special case of the classical Gierer-Mienhardt problem,

(4)

It should be remarked, however, that this case is less special than suggested by comparing (3) to (4). In fact, (4) can be seen as a prototypical system: under certain (generic) conditions equation (3) can be scaled into a *normal form* of the type (4) [3]. Essential in the derivation of the normal form is that both the -component as well as the -component of the pulse solution to (3) scale with a certain negative power of as , i.e. the amplitude of the pulse is in general asymptotically large [3].

**Theorem 1.** [3] *For any there exists an such that for all there exists a homoclinic pulse solution to (4). Both components are of , i.e. both and exist (and are not 0). Moreover, , the homoclinic solution of the associated scalar limit problem (1) with and .*

See Figure 1. The proof of this theorem is based on the ideas of *geometric singular perturbation theory*, see [9].

**Theorem 2.** [3] *The homoclinic pulse solution of (4) is unstable for , and spectrally stable for .*

The proof of this result relies heavily on the *Evans function approach* as was developed in [1]. This method was extended in [4] to systems of the type (3), in the context of an explicit model problem - the Gray-Scott equation. Later, this method has been generalized, so that it is possible to consider the general equation (3). Note that one can go from a situation where the above intuitive argument *(ii)* is valid to a bifurcation that contradicts the intuition, by varying the parameter : if is small enough there is a unstable eigenvalue that merges with the unstable eigenvalue of the scalar limit problem (2) in the limit [3]. However, at a certain critical value merges with another real (positive) eigenvalue and a pair of complex conjugated eigenvalues is formed. This pair crosses the imaginary axis as passes through . Furthermore, it follows from the methods developed in [4,3] that the number of eigenvalues of the linearized stability problem associated to (4) is , two of which can be complex, one more than that of the limit problem (2), which only has real eigenvalues. Hence, the relation between (4) and its scalar limit (1) with is more singular than expected at first sight.